Incentive Mechanisms in Edge Learning Systems

2022 ◽  
pp. 159-170
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yu Qiao ◽  
Jun Wu ◽  
Hao Cheng ◽  
Zilan Huang ◽  
Qiangqiang He ◽  
...  

In the age of the development of artificial intelligence, we face the challenge on how to obtain high-quality data set for learning systems effectively and efficiently. Crowdsensing is a new powerful tool which will divide tasks between the data contributors to achieve an outcome cumulatively. However, it arouses several new challenges, such as incentivization. Incentive mechanisms are significant to the crowdsensing applications, since a good incentive mechanism will attract more workers to participate. However, existing mechanisms failed to consider situations where the crowdsourcer has to hire capacitated workers or workers from multiregions. We design two objectives for the proposed multiregion scenario, namely, weighted mean and maximin. The proposed mechanisms maximize the utility of services provided by a selected data contributor under both constraints approximately. Also, extensive simulations are conducted to verify the effectiveness of our proposed methods.


Author(s):  
Roland Brünken ◽  
Susan Steinbacher ◽  
Jan L. Plass ◽  
Detlev Leutner

Abstract. In two pilot experiments, a new approach for the direct assessment of cognitive load during multimedia learning was tested that uses dual-task methodology. Using this approach, we obtained the same pattern of cognitive load as predicted by cognitive load theory when applied to multimedia learning: The audiovisual presentation of text-based and picture-based learning materials induced less cognitive load than the visual-only presentation of the same material. The findings confirm the utility of dual-task methodology as a promising approach for the assessment of cognitive load induced by complex multimedia learning systems.


2016 ◽  
Vol 24 (1) ◽  
pp. 163
Author(s):  
Hee-Chan Kang ◽  
Sang-Whan Lho
Keyword(s):  

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.


2020 ◽  
Vol 26 (6) ◽  
pp. 1392-1413
Author(s):  
S.V. Ratner

Subject. This article discusses the effectiveness of government programmes to support renewable energy and whether they should continue to be implemented. Objectives. The article aims to conduct a comprehensive analysis of the changes in solar and wind power projects under the State support programme within the period from 2014 to 2019 and assess the effectiveness of the acting incentive mechanisms. Methods. For the study, I used the Learning-by-Doing theory and Project Management principles and methods. Results. The article proposes to consider the local content of the projects implemented as the key effectiveness indicator of the renewable energy support programme in Russia. For solar projects, this figure is currently significantly higher than the planned one, and it corresponds to the planned one for wind projects. In general, therefore, the programme can be considered effective. Conclusions. Further improvements in renewable energy support mechanisms should take into account the need to drastically increase the pace of training in the full cycle of the renewable energy project, including the operation phase of generating equipment and the supply of electricity to the grid.


2020 ◽  
Author(s):  
Farida Hanun

This study aims to obtain a description related to the learning of PAI by using ICT and how the impact of the use of ICT on PAI learning systems in the classroom. The research method uses a qualitative approach in the integrated Islamic high school Ummul Quro Bogor, West Java. The results showed that a) there were four stages of using ICT in the learning process, namely; emerging, applying, integrating dan transforming. PAI teachers are already at the integrating stage. In other words, ICT has been integrated into the PAI learning curriculum. b) supporting factors for the use of ICT are the existence of ICT support facilities, the availability of qualified educators, the commitment of the school to implement ICT in every PAI learning. c) Inhibiting factors in the use of ICT are aspects of financing ICT facilities require a large budget. Some elderly teachers have difficulty using ICT in the learning process. Besides, the internet network is unstable. d) The impact of the use of ICT is very significant on PAI learning process. e) the existence of ICT devices not only as a support but already as an important component in the education system. The research led to the recommendation of the need for government support in the form of concern for ICT in terms of policies, facilities, workforce, budget, and organizing training in the use of ICT for PAI teachers to improve their professionalism. Therefore, further research is suggested regarding the effectiveness of the use of ICT in the learning process of PAI.


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